Search results for: Fully spatial signal processing

Authors: Asif Ekbal, Sivaji Bandyopadhyay

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Named Entity Recognition (NER) aims to classify each word of a document into predefined target named entity classes and is now-a-days considered to be fundamental for many Natural Language Processing (NLP) tasks such as information retrieval, machine translation, information extraction, question answering systems and others. This paper reports about the development of a NER system for Bengali and Hindi using Support Vector Machine (SVM). Though this state of the art machine learning technique has been widely applied to NER in several well-studied languages, the use of this technique to Indian languages (ILs) is very new. The system makes use of the different contextual information of the words along with the variety of features that are helpful in predicting the four different named (NE) classes, such as Person name, Location name, Organization name and Miscellaneous name. We have used the annotated corpora of 122,467 tokens of Bengali and 502,974 tokens of Hindi tagged with the twelve different NE classes 1, defined as part of the IJCNLP-08 NER Shared Task for South and South East Asian Languages (SSEAL) 2. In addition, we have manually annotated 150K wordforms of the Bengali news corpus, developed from the web-archive of a leading Bengali newspaper. We have also developed an unsupervised algorithm in order to generate the lexical context patterns from a part of the unlabeled Bengali news corpus. Lexical patterns have been used as the features of SVM in order to improve the system performance. The NER system has been tested with the gold standard test sets of 35K, and 60K tokens for Bengali, and Hindi, respectively. Evaluation results have demonstrated the recall, precision, and f-score values of 88.61%, 80.12%, and 84.15%, respectively, for Bengali and 80.23%, 74.34%, and 77.17%, respectively, for Hindi. Results show the improvement in the f-score by 5.13% with the use of context patterns. Statistical analysis, ANOVA is also performed to compare the performance of the proposed NER system with that of the existing HMM based system for both the languages.

Keywords: Named Entity (NE), Named Entity Recognition (NER), Support Vector Machine (SVM), Bengali, Hindi.

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Authors: F. Lops, G. Disciglio, A. Carlucci, G. Gatta, L. Frabboni, A. Tarantino, E. Tarantino

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Phelipanche ramosa L. Pomel is a root holoparasitic weed plant of many cultivations, particularly of tomato (Lycopersicum esculentum L.) crop. In Italy, Phelipanche problem is increasing, both in density and in acreage. The biological control of this parasitic weed involves the use of living organisms as numerous fungi and bacteria that can infect the parasitic weed, while it may improve the crop growth. This paper deals with the biocontrol with microorganism, including Arbuscular mycorrhizal (AM) fungi and fungal pathogens as Fusarium oxisporum spp. Colonization of crop roots by AM fungi can provide protection of crops against parasitic weeds because of a reduction in their seed germination and attachment, while F. oxisporum, isolated from diseased broomrape tubercles, proved to be highly virulent on P. ramosa. The experimental trial was carried out in open field at Foggia province (Apulia Region, Southern Italy), during the spring-summer season 2016, in order to evaluate the effect of four biological treatments: AM fungi and Fusarium oxisporum applied in the soil alone or combined together, and Rizosum Max^® product, compared with the untreated control, to reduce the P. ramosa infestation in processing tomato crop. The principal results to be drawn from this study under field condition, in contrast of those reported previously under laboratory and greenhouse conditions, show that both AM fungi and F. oxisporum do not provide the reduction of the number of emerged shoots of P. ramosa. This can arise probably from the low efficacy seedling of the agent pathogens for the control of this parasite in the field. On the contrary, the Rizosum Max^® product, containing AM fungi and some rizophere bacteria combined with several minerals and organic substances, appears to be most effective for the reduction of P. ramosa infestation.

Keywords: Arbuscular mycorrhizal fungi, biocontrol methods, Phelipanche ramosa, F. oxisporum spp.

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Authors: G. Disciglio, F. Lops, A. Carlucci, G. Gatta, A. Tarantino, E. Tarantino

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Phelipanche ramosa is the most damaging obligate flowering parasitic weed on wide species of cultivated plants. The semi-arid regions of the world are considered the main centers of this parasitic plant that causes heavy infestation. This is due to its production of high numbers of seeds (up to 200,000) that remain viable for extended periods (up to 20 years). In this study, 13 treatments for the control of Phelipanche were carried out, which included agronomic, chemical, and biological treatments and the use of resistant plant methods. In 2014, a trial was performed at the Department of Agriculture, Food and Environment, University of Foggia (southern Italy), on processing tomato (cv ‘Docet’) grown in pots filled with soil taken from a field that was heavily infested by P. ramosa). The tomato seedlings were transplanted on May 8, 2014, into a sandy-clay soil (USDA). A randomized block design with 3 replicates (pots) was adopted. During the growing cycle of the tomato, at 70, 75, 81 and 88 days after transplantation, the number of P. ramosa shoots emerged in each pot was determined. The tomato fruit were harvested on August 8, 2014, and the quantitative and qualitative parameters were determined. All of the data were subjected to analysis of variance (ANOVA) using the JMP software (SAS Institute Inc. Cary, NC, USA), and for comparisons of means (Tukey's tests). The data show that each treatment studied did not provide complete control against P. ramosa. However, the virulence of the attacks was mitigated by some of the treatments tried: radicon biostimulant, compost activated with Fusarium, mineral fertilizer nitrogen, sulfur, enzone, and the resistant tomato genotype. It is assumed that these effects can be improved by combining some of these treatments with each other, especially for a gradual and continuing reduction of the “seed bank” of the parasite in the soil.

Keywords: Control methods, Phelipanche ramosa, tomato crop.

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Authors: Mustafa Kavraz

Abstract:

This study investigated the differences in the objective parameters of sound depending on the changes in the lengths of the lateral surfaces of a space and on the replacement of the sound absorbers that are placed on these surfaces. To this end, three models of room were chosen. The widths and heights of these rooms were the same but the lengths of the rooms were changed. The smallest room was 8 m. wide and 10 m. long. The lengths of the other two rooms were 15 m. and 20 m. For each model, the differences in the objective parameters of sound were determined by keeping all the material in the space intact and by changing only the positions of the sound absorbers that were placed on the walls. The sound absorbers that were used on the walls were of two different sizes. The sound absorbers that were placed on the walls were 4 m and 8 m. long and story-height (3 m.). In all model room types, the sound absorbers were placed on the long walls in three different ways: at the end of the long walls where the long walls meet the front wall; at the end of the long walls where the long walls meet the back wall; and in the middle part of the long walls. Except for the specially placed sound absorbers, the ground, wall and ceiling surfaces were covered with three different materials. There were no constructional elements such as doors and windows on the walls. On the surfaces, the materials specified in the Odeon 10 material library were used as coating material. Linoleum was used as flooring material, painted plaster as wall coating material and gypsum boards as ceiling covering (2 layers with a total of 32 mm. thickness). These were preferred due to the fact that they are the commonly used materials for these purposes. This study investigated the differences in the objective parameters of sound depending on the changes in the lengths of the lateral surfaces of a space and on the replacement of the sound absorbers that are placed on these surfaces. To this end, three models of room were chosen. The widths and heights of these rooms were the same but the lengths of the rooms were changed. The smallest room was 8 m. wide and 10 m. long. The lengths of the other two rooms were 15 m. and 20 m. For each model, the differences in the objective parameters of sound were determined by keeping all the material in the space intact and by changing only the positions of the sound absorbers that were placed on the walls. The sound absorbers that were used on the walls were of two different sizes. The sound absorbers that were placed on the walls were 4 m and 8 m. long and story-height (3 m.). In all model room types, the sound absorbers were placed on the long walls in three different ways: at the end of the long walls where the long walls meet the front wall; at the end of the long walls where the long walls meet the back wall; and in the middle part of the long walls. Except for the specially placed sound absorbers, the ground, wall and ceiling surfaces were covered with three different materials. There were no constructional elements such as doors and windows on the walls. On the surfaces, the materials specified in the Odeon 10 material library were used as coating material. Linoleum was used as flooring material, painted plaster as wall coating material and gypsum boards as ceiling covering (2 layers with a total of 32 mm. thickness). These were preferred due to the fact that they are the commonly used materials for these purposes.

Keywords: Jnd, objective parameters of sound, room model, sound absorber.

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Authors: Krasimira Georgieva, Yordan Denev

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Many of thermosetting resins have application only in filled state, reinforced with different mineral fillers. The co-filling of polymers with mineral filler and gases creates a possibility for production of polymer composites materials with low density. This processing leads to forming of new materials – gas-filled plastics (polymer foams). The properties of these materials are determined mainly by the shape and size of internal structural elements (pores). The interactions on the phase boundaries have influence on the materials properties too. In the present work, the gas-filled urea-formaldehyde resins were reinforced by waste phosphogypsum. The waste phosphogypsum (CaSO₄.2H₂O) is a solid by-product in wet phosphoric acid production processes. The values of the interactions polymer-filler were increased by using two modifying agents: polyvinyl acetate for polymer matrix and sodium metasilicate for filler. Technological methods for gas-filling and recipes of urea-formaldehyde based materials with apparent density 20-120 kg/m³ were developed. The heat conductivity of the samples is between 0.024 and 0.029 W/m^oK. Tensile analyses were carried out at 10 and 50% deformation and show values 0.01-0.14 MPa and 0.01-0.09 MPa, respectively. The apparent density of obtained materials is between 20 and 92 kg/m³. The changes in the tensile properties and density of these materials according to sodium metasilicate content were studied too. The mechanism of phosphogypsum adsorption modification was studied using methods of FT-IR spectroscopy. The structure of the gas-filled urea-formaldehyde resins was described by results of electron scanning microscopy at three different magnification ratios – x50, x150 and x 500. The aim of present work is to study the possibility of the usage of phosphogypsum as mineral filler for urea-formaldehyde resins and development of a technology for the production of gas-filled reinforced polymer composite materials. The structure and the properties of obtained composite materials are suitable for thermal and sound insulation applications.

Keywords: Gas-filled thermosets, mechanical properties, phosphogypsum, urea-formaldehyde resins.

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Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

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Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of big data technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centres or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through VADER and RoBERTa model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and Term Frequency – Inverse Document Frequency (TFIDF) Vectorization and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide if the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: Counter vectorization, Convolutional Neural Network, Crawler, data technology, Long Short-Term Memory, LSTM, Web Scraping, sentiment analysis.

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Authors: K. A. Ghazaryan, H. S. Movsesyan, N. P. Ghazaryan

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The present study was aimed in assessing the heavy metal pollution of the soils around Agarak copper-molybdenum mine complex and related environmental risks. This mine complex is located in the south-east part of Armenia, and the present study was conducted in 2013. The soils of the five riskiest sites of this region were studied: surroundings of the open mine, the sites adjacent to processing plant of Agarak copper-molybdenum mine complex, surroundings of Darazam active tailing dump, the recultivated tailing dump of “ravine - 2”, and the recultivated tailing dump of “ravine - 3”. The mountain cambisol was the main soil type in the study sites. The level of soil contamination by heavy metals was assessed by Contamination factors (Cf), Degree of contamination (Cd), Geoaccumulation index (I-geo) and Enrichment factor (EF). The distribution pattern of trace metals in the soil profile according to Cf, Cd, I-geo and EF values shows that the soil is much polluted. Almost in all studied sites, Cu, Mo, Pb, and Cd were the main polluting heavy metals, and this was conditioned by Agarak copper-molybdenum mine complex activity. It is necessary to state that the pollution problem becomes pressing as some parts of these highly polluted region are inhabited by population, and agriculture is highly developed there; therefore, heavy metals can be transferred into human bodies through food chains and have direct influence on public health. Since the induced pollution can pose serious threats to public health, further investigations on soil and vegetation pollution are recommended. Finally, Cf calculating based on distance from the pollution source and the wind direction can provide more reasonable results.

Keywords: Agarak copper-molybdenum mine complex, heavy metals, soil contamination, enrichment factor, Armenia.

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Authors: N. Porzionato, M. Mantiñan, E. Bussi, S. Grinberg, R. Gutierrez, G. Curutchet

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This work sets out to debate the tensions involved in the processes of contamination and self-purification in the urban space, particularly in the streams that run through the Buenos Aires metropolitan area. For much of their course, those streams are piped; their waters do not come into contact with the outdoors until they have reached deeply impoverished urban areas with high levels of environmental contamination. These are peripheral zones that, until thirty years ago, were marshlands and fields. They are now densely populated areas largely lacking in urban infrastructure. The Cárcova neighborhood, where this project is underway, is in the José León Suárez section of General San Martín county, Buenos Aires province. A stretch of José León Suarez canal crosses the neighborhood. Starting upstream, this canal carries pollutants due to the sewage and industrial waste released into it. Further downstream, in the neighborhood, domestic drainage is poured into the stream. In this paper, we formulate a hypothesis diametrical to the one that holds that these neighborhoods are the primary source of contamination, suggesting instead that in the stretch of the canal that runs through the neighborhood the stream’s waters are actually cleaned and the sediments accumulate pollutants. Indeed, the stretches of water that runs through these neighborhoods act as water processing plants for the metropolis. This project has studied the different organic-load polluting contributions to the water in a certain stretch of the canal, the reduction of that load over the course of the canal, and the incorporation of pollutants into the sediments. We have found that the surface water has considerable ability to self-purify, mostly due to processes of sedimentation and adsorption. The polluting load is accumulated in the sediments where that load stabilizes slowly by means of anaerobic processes. In this study, we also investigated the risks of sediment management and the use of the processes studied here in controlled conditions as tools of environmental restoration.

Keywords: Bioremediation, pollutants, sediments, urban streams.

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Authors: Mareli Hattingh, I. Jaco Van der Walt, Frans B. Waanders

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A waste-to-energy plasma system was designed by Necsa for commercial use to create electricity from unsorted municipal waste. Fly ash particles must be removed from the syngas stream at operating temperatures of 1000 °C and recycled back into the reactor for complete combustion. A 2D2D high efficiency cyclone separator was chosen for this purpose. During this study, two cyclone design methods were explored: The Classic Empirical Method (smaller cyclone) and the Flow Characteristics Method (larger cyclone). These designs were optimized with regard to efficiency, so as to remove at minimum 90% of the fly ash particles of average size 10 μm by 50 μm. Wood was used as feed source at a concentration of 20 g/m³ syngas. The two designs were then compared at room temperature, using Perspex test units and three feed gases of different densities, namely nitrogen, helium and air. System conditions were imitated by adapting the gas feed velocity and particle load for each gas respectively. Helium, the least dense of the three gases, would simulate higher temperatures, whereas air, the densest gas, simulates a lower temperature. The average cyclone efficiencies ranged between 94.96% and 98.37%, reaching up to 99.89% in individual runs. The lowest efficiency attained was 94.00%. Furthermore, the design of the smaller cyclone proved to be more robust, while the larger cyclone demonstrated a stronger correlation between its separation efficiency and the feed temperatures. The larger cyclone can be assumed to achieve slightly higher efficiencies at elevated temperatures. However, both design methods led to good designs. At room temperature, the difference in efficiency between the two cyclones was almost negligible. At higher temperatures, however, these general tendencies are expected to be amplified so that the difference between the two design methods will become more obvious. Though the design specifications were met for both designs, the smaller cyclone is recommended as default particle separator for the plasma system due to its robust nature.

Keywords: Cyclone, design, plasma, renewable energy, solid separation, waste processing.

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Authors: C. Silveira, A. Ascenso, J. Ferreira, A. I. Miranda, P. Tuccella, G. Curci

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Poor air quality is one of the main environmental causes of premature deaths worldwide, and mainly in cities, where the majority of the population lives. It is a consequence of successive land cover (LC) and use changes, as a result of the intensification of human activities. Knowing these landscape modifications in a comprehensive spatiotemporal dimension is, therefore, essential for understanding variations in air pollutant concentrations. In this sense, the use of air quality models is very useful to simulate the physical and chemical processes that affect the dispersion and reaction of chemical species into the atmosphere. However, the modelling performance should always be evaluated since the resolution of the input datasets largely dictates the reliability of the air quality outcomes. Among these data, the updated LC is an important parameter to be considered in atmospheric models, since it takes into account the Earth’s surface changes due to natural and anthropic actions, and regulates the exchanges of fluxes (emissions, heat, moisture, etc.) between the soil and the air. This work aims to evaluate the performance of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), when different LC classifications are used as an input. The influence of two LC classifications was tested: i) the 24-classes USGS (United States Geological Survey) LC database included by default in the model, and the ii) CLC (Corine Land Cover) and specific high-resolution LC data for Portugal, reclassified according to the new USGS nomenclature (33-classes). Two distinct WRF-Chem simulations were carried out to assess the influence of the LC on air quality over Europe and Portugal, as a case study, for the year 2015, using the nesting technique over three simulation domains (25 km², 5 km² and 1 km² horizontal resolution). Based on the 33-classes LC approach, particular emphasis was attributed to Portugal, given the detail and higher LC spatial resolution (100 m x 100 m) than the CLC data (5000 m x 5000 m). As regards to the air quality, only the LC impacts on tropospheric ozone concentrations were evaluated, because ozone pollution episodes typically occur in Portugal, in particular during the spring/summer, and there are few research works relating to this pollutant with LC changes. The WRF-Chem results were validated by season and station typology using background measurements from the Portuguese air quality monitoring network. As expected, a better model performance was achieved in rural stations: moderate correlation (0.4 – 0.7), BIAS (10 – 21µg.m^-3) and RMSE (20 – 30 µg.m^-3), and where higher average ozone concentrations were estimated. Comparing both simulations, small differences grounded on the Leaf Area Index and air temperature values were found, although the high-resolution LC approach shows a slight enhancement in the model evaluation. This highlights the role of the LC on the exchange of atmospheric fluxes, and stresses the need to consider a high-resolution LC characterization combined with other detailed model inputs, such as the emission inventory, to improve air quality assessment.

Keywords: Land cover, tropospheric ozone, WRF-Chem, air quality assessment.

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

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Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: Affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, Signal Detection Theory, student engagement.

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Authors: Siddhartha Bhattacharyya, Paramartha Dutta, Ujjwal Maulik, Prashanta Kumar Nandi

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The paper describes a self supervised parallel self organizing neural network (PSONN) architecture for true color image segmentation. The proposed architecture is a parallel extension of the standard single self organizing neural network architecture (SONN) and comprises an input (source) layer of image information, three single self organizing neural network architectures for segmentation of the different primary color components in a color image scene and one final output (sink) layer for fusion of the segmented color component images. Responses to the different shades of color components are induced in each of the three single network architectures (meant for component level processing) by applying a multilevel version of the characteristic activation function, which maps the input color information into different shades of color components, thereby yielding a processed component color image segmented on the basis of the different shades of component colors. The number of target classes in the segmented image corresponds to the number of levels in the multilevel activation function. Since the multilevel version of the activation function exhibits several subnormal responses to the input color image scene information, the system errors of the three component network architectures are computed from some subnormal linear index of fuzziness of the component color image scenes at the individual level. Several multilevel activation functions are employed for segmentation of the input color image scene using the proposed network architecture. Results of the application of the multilevel activation functions to the PSONN architecture are reported on three real life true color images. The results are substantiated empirically with the correlation coefficients between the segmented images and the original images.

Keywords: Colour image segmentation, fuzzy set theory, multi-level activation functions, parallel self-organizing neural network.

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Authors: Padmanabhan Balasubramanian, C. Hari Narayanan

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This paper discusses a new, systematic approach to the synthesis of a NP-hard class of non-regenerative Boolean networks, described by FON[FOFF]={mi}[{Mi}], where for every mj[Mj]∈{mi}[{Mi}], there exists another mk[Mk]∈{mi}[{Mi}], such that their Hamming distance HD(mj, mk)=HD(Mj, Mk)=O(n), (where 'n' represents the number of distinct primary inputs). The method automatically ensures exact minimization for certain important selfdual functions with 2n-1 points in its one-set. The elements meant for grouping are determined from a newly proposed weighted incidence matrix. Then the binary value corresponding to the candidate pair is correlated with the proposed binary value matrix to enable direct synthesis. We recommend algebraic factorization operations as a post processing step to enable reduction in literal count. The algorithm can be implemented in any high level language and achieves best cost optimization for the problem dealt with, irrespective of the number of inputs. For other cases, the method is iterated to subsequently reduce it to a problem of O(n-1), O(n-2),.... and then solved. In addition, it leads to optimal results for problems exhibiting higher degree of adjacency, with a different interpretation of the heuristic, and the results are comparable with other methods. In terms of literal cost, at the technology independent stage, the circuits synthesized using our algorithm enabled net savings over AOI (AND-OR-Invert) logic, AND-EXOR logic (EXOR Sum-of- Products or ESOP forms) and AND-OR-EXOR logic by 45.57%, 41.78% and 41.78% respectively for the various problems. Circuit level simulations were performed for a wide variety of case studies at 3.3V and 2.5V supply to validate the performance of the proposed method and the quality of the resulting synthesized circuits at two different voltage corners. Power estimation was carried out for a 0.35micron TSMC CMOS process technology. In comparison with AOI logic, the proposed method enabled mean savings in power by 42.46%. With respect to AND-EXOR logic, the proposed method yielded power savings to the tune of 31.88%, while in comparison with AND-OR-EXOR level networks; average power savings of 33.23% was obtained.

Keywords: AOI logic, ESOP, AND-OR-EXOR, Incidencematrix, Hamming distance.

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Authors: Samuel Kaspi, Sitalakshmi Venkatraman

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In-memory database systems are becoming popular due to the availability and affordability of sufficiently large RAM and processors in modern high-end servers with the capacity to manage large in-memory database transactions. While fast and reliable inmemory systems are still being developed to overcome cache misses, CPU/IO bottlenecks and distributed transaction costs, disk-based data stores still serve as the primary persistence. In addition, with the recent growth in multi-tenancy cloud applications and associated security concerns, many organisations consider the trade-offs and continue to require fast and reliable transaction processing of diskbased database systems as an available choice. For these organizations, the only way of increasing throughput is by improving the performance of disk-based concurrency control. This warrants a hybrid database system with the ability to selectively apply an enhanced disk-based data management within the context of inmemory systems that would help improve overall throughput. The general view is that in-memory systems substantially outperform disk-based systems. We question this assumption and examine how a modified variation of access invariance that we call enhanced memory access, (EMA) can be used to allow very high levels of concurrency in the pre-fetching of data in disk-based systems. We demonstrate how this prefetching in disk-based systems can yield close to in-memory performance, which paves the way for improved hybrid database systems. This paper proposes a novel EMA technique and presents a comparative study between disk-based EMA systems and in-memory systems running on hardware configurations of equivalent power in terms of the number of processors and their speeds. The results of the experiments conducted clearly substantiate that when used in conjunction with all concurrency control mechanisms, EMA can increase the throughput of disk-based systems to levels quite close to those achieved by in-memory system. The promising results of this work show that enhanced disk-based systems facilitate in improving hybrid data management within the broader context of in-memory systems.

Keywords: Concurrency control, disk-based databases, inmemory systems, enhanced memory access (EMA).

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Authors: Hritwik Ghosh, Irfan Sadiq Rahat, Sachi Nandan Mohanty, J. V. R. Ravindra, Abdus Sobur

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In the rapidly evolving landscape of medical diagnostics, the early detection and accurate classification of skin cancer remain paramount for effective treatment outcomes. This research delves into the transformative potential of artificial intelligence (AI), specifically deep learning (DL), as a tool for discerning and categorizing various skin conditions. Utilizing a diverse dataset of 3,000 images, representing nine distinct skin conditions, we confront the inherent challenge of class imbalance. This imbalance, where conditions like melanomas are over-represented, is addressed by incorporating class weights during the model training phase, ensuring an equitable representation of all conditions in the learning process. Our approach presents a hybrid model, amalgamating the strengths of two renowned convolutional neural networks (CNNs), VGG16 and ResNet50. These networks, pre-trained on the ImageNet dataset, are adept at extracting intricate features from images. By synergizing these models, our research aims to capture a holistic set of features, thereby bolstering classification performance. Preliminary findings underscore the hybrid model's superiority over individual models, showcasing its prowess in feature extraction and classification. Moreover, the research emphasizes the significance of rigorous data pre-processing, including image resizing, color normalization, and segmentation, in ensuring data quality and model reliability. In essence, this study illuminates the promising role of AI and DL in revolutionizing skin cancer diagnostics, offering insights into its potential applications in broader medical domains.

Keywords: Artificial intelligence, machine learning, deep learning, skin cancer, dermatology, convolutional neural networks, image classification, computer vision, healthcare technology, cancer detection, medical imaging.

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Authors: Saranya Chularee, Tawa Chularee

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Successful intelligence (SI) is the integrated set of the ability needed to attain success in life, within individual-s sociocultural context. People are successfully intelligent by recognizing their strengths and weaknesses. They will find ways to strengthen their weakness and maintain their strength or even improve it. SI people can shape, select, and adapt to the environments by using balance of higher-ordered thinking abilities including; critical, creative, and applicative. Aims: The purposes of this study were to; 1) develop curriculum that promotes SI for nursing students, and 2) study the effectiveness of the curriculum development. Method: Research and Development was a method used for this study. The design was divided into two phases; 1) the curriculum development which composed of three steps (needs assessment, curriculum development and curriculum field trail), and 2) the curriculum implementation. In this phase, a pre-experimental research design (one group pretest-posttest design) was conducted. The sample composed of 49 sophomore nursing students of Boromarajonani College of Nursing, Surin, Thailand who enrolled in Nursing care of Health problem course I in 2011 academic year. Data were carefully collected using 4 instruments; 1) Modified essay questions test (MEQ) 2) Nursing Care Plan evaluation form 3) Group processing observation form (α = 0.74) and 4) Satisfied evaluation form of learning (α = 0.82). Data were analyzed using descriptive statistics and content analysis. Results: The results revealed that the sample had post-test average score of SI higher than pre-test average score (mean difference was 5.03, S.D. = 2.84). Fifty seven percentages of the sample passed the MEQ posttest at the criteria of 60 percentages. Students demonstrated the strategies of how to develop nursing care plan. Overall, students- satisfaction on teaching performance was at high level (mean = 4.35, S.D. = 0.46). Conclusion: This curriculum can promote the attribute of characteristic of SI person and was highly required to be continued.

Keywords: Curriculum Development, Nursing Education, Successful Intelligence, Thinking ability.

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Authors: Disciglio G., Lops F., Carlucci A., Gatta G., Tarantino A., Frabboni L., Carriero F., Cibelli F., Raimondo M. L., Tarantino E.

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The tomato is a very important crop, whose cultivation in the Mediterranean basin is severely affected by the phytoparasitic weed Phelipanche ramosa. The semiarid regions of the world are considered the main areas where this parasitic weed is established causing heavy infestation as it is able to produce high numbers of seeds (up to 500,000 per plant), which remain viable for extended period (more than 20 years). In this paper the results obtained from eleven treatments in order to control this parasitic weed including chemical, agronomic, biological and biotechnological methods compared with the untreated test under two plowing depths (30 and 50 cm) are reported. The split-plot design with 3 replicates was adopted. In 2014 a trial was performed in Foggia province (southern Italy) on processing tomato (cv Docet) grown in the field infested by Phelipanche ramosa. Tomato seedlings were transplant on May 5, on a clay-loam soil. During the growing cycle of the tomato crop, at 56-78 and 92 days after transplantation, the number of parasitic shoots emerged in each plot was detected. At tomato harvesting, on August 18, the major quantity-quality yield parameters were determined (marketable yield, mean weight, dry matter, pH, soluble solids and color of fruits). All data were subjected to analysis of variance (ANOVA) and the means were compared by Tukey's test. Each treatment studied did not provide complete control against Phelipanche ramosa. However, among the different methods tested, some of them which Fusarium, gliphosate, radicon biostimulant and Red Setter tomato cv (improved genotypes obtained by Tilling technology) under deeper plowing (50 cm depth) proved to mitigate the virulence of the Phelipanche ramose attacks. It is assumed that these effects can be improved combining some of these treatments each other, especially for a gradual and continuing reduction of the “seed bank” of the parasite in the soil.

Keywords: Control methods, Phelipanche ramosa, tomato crop.

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Authors: R. Meier, M. Pander

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In accordance with the industry 4.0 concept, manufacturing process steps as well as the materials themselves are going to be more and more digitalized within the next years. The “digital twin” representing the simulated and measured dataset of the (semi-finished) product can be used to control and optimize the individual processing steps and help to reduce costs and expenditure of time in product development, manufacturing, and recycling. In the present work, two material characterization methods based on Lamb waves were evaluated and compared. For demonstration purpose, both methods were shown at a standard industrial product - copper ribbons, often used in photovoltaic modules as well as in high-current microelectronic devices. By numerical approximation of the Rayleigh-Lamb dispersion model on measured phase velocities second order elastic constants (Young’s modulus, Poisson’s ratio) were determined. Furthermore, the effective third order elastic constants were evaluated by applying elastic, “non-destructive”, mechanical stress on the samples. In this way, small microstructural variations due to mechanical preconditioning could be detected for the first time. Both methods were compared with respect to precision and inline application capabilities. Microstructure of the samples was systematically varied by mechanical loading and annealing. Changes in the elastic ultrasound transport properties were correlated with results from microstructural analysis and mechanical testing. In summary, monitoring the elastic material properties of plate-like structures using Lamb waves is valuable for inline and non-destructive material characterization and manufacturing process control. Second order elastic constants analysis is robust over wide environmental and sample conditions, whereas the effective third order elastic constants highly increase the sensitivity with respect to small microstructural changes. Both Lamb wave based characterization methods are fitting perfectly into the industry 4.0 concept.

Keywords: Lamb waves, industry 4.0, process control, elasticity, acoustoelasticity.

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Authors: Chris Fersterer, Col Fay, Tobias Danielmeier, Kat Achterberg, Scott Willis

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New Zealand, an island nation, has an extensive coastline peppered with small communities of iconic buildings known as Bachs. Post WWII, these modest buildings were constructed by their owners as retreats and generally were small, low cost, often using recycled material and often they fell below current acceptable building standards. In the latter part of the 20^th century, real estate prices in many of these communities remained low and these areas became permanent residences for people attracted to this affordable lifestyle choice. The Blueskin Resilient Communities Trust (BRCT) is an organisation that recognises the vulnerability of communities in low lying settlements as now being prone to increased flood threat brought about by climate change and sea level rise. Some of the inhabitants of Blueskin Bay, Otago, NZ have already found their properties to be un-insurable because of increased frequency of flood events and property values have slumped accordingly. Territorial authorities also acknowledge this increased risk and have created additional compliance measures for new buildings that are less than 2 m above tidal peaks. Community resilience becomes an additional concern where inhabitants are attracted to a lifestyle associated with a specific location and its people when this lifestyle is unable to be met in a suburban or city context. Traditional models of social housing fail to provide the sense of community connectedness and identity enjoyed by the current residents of Blueskin Bay. BRCT have partnered with the Otago Polytechnic Design School to design a new form of community housing that can react to this environmental change. It is a longitudinal project incorporating participatory approaches as a means of getting people ‘on board’, to understand complex systems and co-develop solutions. In the first period, they are seeking industry support and funding to develop a transportable and fully self-contained housing model that exploits current technologies. BRCT also hope that the building will become an educational tool to highlight climate change issues facing us today. This paper uses the Climate Safe House (CSH) as a case study for education in architectural sustainability through experiential learning offered as part of the Otago Polytechnics Bachelor of Design. Students engage with the project with research methodologies, including site surveys, resident interviews, data sourced from government agencies and physical modelling. The process involves collaboration across design disciplines including product and interior design but also includes connections with industry, both within the education institution and stakeholder industries introduced through BRCT. This project offers a rich learning environment where students become engaged through project based learning within a community of practice, including architecture, construction, energy and other related fields. The design outcomes are expressed in a series of public exhibitions and forums where community input is sought in a truly participatory process.

Keywords: Community resilience, problem based learning, project based learning, case study.

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Authors: Tanvi P. Medshinge, Prasad Vaidya, Monisha E. Royan

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In India, cooling loads in residential sector is a major contributor to its total energy consumption. Due to the increasing cooling need, the market penetration of air-conditioners is further expected to rise. Natural Ventilation (NV), however, possesses great potential to save significant energy consumption especially for residential buildings in moderate climates. As multifamily residential apartment buildings are designed by repetitive use of prototype designs, deriving individual NV based design prototype solutions for a combination of different wind incidence angles and orientations would provide significant opportunity to address the rise in cooling loads by residential sector. This paper presents the results of NV performance of a selected prototype apartment design with a cluster of four units in Pune, India, and an attempt to improve the NV performance through design modifications. The water table apparatus, a physical modelling tool, is used to study the flow patterns and simulate wind-induced NV performance. Quantification of NV performance is done by post processing images captured from video recordings in terms of percentage of area with good and poor access to ventilation. NV performance of the existing design for eight wind incidence angles showed that of the cluster of four units, the windward units showed good access to ventilation for all rooms, and the leeward units had lower access to ventilation with the bedrooms in the leeward units having the least access. The results showed improved performance in all the units for all wind incidence angles to more than 80% good access to ventilation. Some units showed an additional improvement to more than 90% good access to ventilation. This process of design and performance evaluation improved some individual units from 0% to 100% for good access to ventilation. The results demonstrate the ease of use and the power of the water table apparatus for performance-based design to simulate wind induced NV.  

Keywords: Prototype design, water table apparatus, NV, wind incidence angles, simulations, fluid dynamics.

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Authors: Moustafa Osman Mohammed

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This paper introduces topological order in descried social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. Topological order is important in describing the physical systems for exploiting optical systems and improving photonic devices. The stats of topologically order have some interesting properties of topological degeneracy and fractional statistics that reveal the entanglement origin of topological order, etc. Topological ideas in photonics form exciting developments in solid-state materials, that being; insulating in the bulk, conducting electricity on their surface without dissipation or back-scattering, even in the presence of large impurities. A specific type of autopoiesis system is interrelated to the main categories amongst existing groups of the ecological phenomena interaction social and medical sciences. The hypothesis, nevertheless, has a nonlinear interaction with its natural environment ‘interactional cycle’ for exchange photon energy with molecules without changes in topology (i.e., chemical transformation into products do not propagate any changes or variation in the network topology of physical configuration). The engineering topology of a biosensor is based on the excitation boundary of surface electromagnetic waves in photonic band gap multilayer films. The device operation is similar to surface Plasmonic biosensors in which a photonic band gap film replaces metal film as the medium when surface electromagnetic waves are excited. The use of photonic band gap film offers sharper surface wave resonance leading to the potential of greatly enhanced sensitivity. So, the properties of the photonic band gap material are engineered to operate a sensor at any wavelength and conduct a surface wave resonance that ranges up to 470 nm. The wavelength is not generally accessible with surface Plasmon sensing. Lastly, the photonic band gap films have robust mechanical functions that offer new substrates for surface chemistry to understand the molecular design structure, and create sensing chips surface with different concentrations of DNA sequences in the solution to observe and track the surface mode resonance under the influences of processes that take place in the spectroscopic environment. These processes led to the development of several advanced analytical technologies, which are automated, real-time, reliable, reproducible and cost-effective. This results in faster and more accurate monitoring and detection of biomolecules on refractive index sensing, antibody–antigen reactions with a DNA or protein binding. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other in order to form unique spatial structure and dynamics of biological molecules for providing the environment mutual contribution in investigation of changes due the pathogenic archival architecture of cell clusters.

Keywords: autopoiesis, engineering topology, photonic system molecular structure, biosensor

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Authors: Mohanapriya Subramanian, V. Raj

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Direct methanol fuel cells (DMFCs) are considered to be one of the most promising candidates for portable and stationary applications in the view of their advantages such as high energy density, easy manipulation, high efficiency and they operate with liquid fuel which could be used without requiring any fuel-processing units. Electrolyte membrane of DMFC plays a key role as a proton conductor as well as a separator between electrodes. Increasing concern over environmental protection, biopolymers gain tremendous interest owing to their eco-friendly bio-degradable nature. Pectin is a natural anionic polysaccharide which plays an essential part in regulating mechanical behavior of plant cell wall and it is extracted from outer cells of most of the plants. The aim of this study is to develop and demonstrate pectin based polymer composite membranes as methanol impermeable polymer electrolyte membranes for DMFCs. Pectin based nanocomposites membranes are prepared by solution-casting technique wherein pectin is blended with chitosan followed by the addition of optimal amount of sulphonic acid modified Titanium dioxide nanoparticle (S-TiO2). Nanocomposite membranes are characterized by Fourier Transform-Infra Red spectroscopy, Scanning electron microscopy, and Energy dispersive spectroscopy analyses. Proton conductivity and methanol permeability are determined into order to evaluate their suitability for DMFC application. Pectin-chitosan blends endow with a flexible polymeric network which is appropriate to disperse rigid S-TiO2 nanoparticles. Resulting nanocomposite membranes possess adequate thermo-mechanical stabilities as well as high charge-density per unit volume. Pectin-chitosan natural polymeric nanocomposite comprising optimal S-TiO2 exhibits good electrochemical selectivity and therefore desirable for DMFC application.

Keywords: Biopolymers, fuel cells, nanocomposite, methanol crossover.

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Authors: Goksen Arik, Mihriban Korukluoglu

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Lactic acid bacteria (LAB) and some yeast species are common microorganisms found in dairy products and most of them are responsible for the fermentation of foods. Such cultures are isolated and used as a starter culture in the food industry because of providing standardisation of the final product during the food processing. Choice of starter culture is the most important step for the production of fermented food. Isolated LAB and yeast cultures which have the ability to create a biofilm layer can be preferred as a starter in the food industry. The biofilm formation could be beneficial to extend the period of usage time of microorganisms as a starter. On the other hand, it is an undesirable property in pathogens, since biofilm structure allows a microorganism become more resistant to stress conditions such as antibiotic presence. It is thought that the resistance mechanism could be turned into an advantage by promoting the effective microorganisms which are used in the food industry as starter culture and also which have potential to stimulate the gastrointestinal system. Development of the biofilm layer is observed in some LAB and yeast strains. The resistance could make LAB and yeast strains dominant microflora in the human gastrointestinal system; thus, competition against pathogen microorganisms can be provided more easily. Based on this circumstance, in the study, 10 LAB and 10 yeast strains were isolated from various dairy products, such as cheese, yoghurt, kefir, and cream. Samples were obtained from farmer markets and bazaars in Bursa, Turkey. As a part of this research, all isolated strains were identified and their ability of biofilm formation was detected with two different methods and compared with each other. The first goal of this research was to determine whether isolates have the potential for biofilm production, and the second was to compare the validity of two different methods, which are known as “Tube method” and “96-well plate-based method”. This study may offer an insight into developing a point of view about biofilm formation and its beneficial properties in LAB and yeast cultures used as a starter in the food industry.

Keywords: Biofilm, dairy products, lactic acid bacteria, yeast.

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Authors: Davide D’Aria, Paolo Falcone, Luigi Maggi, Aldo Cero, Giovanni Amoroso

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The paper presents a methodology for real-time structural health monitoring and geophysical applications. The key elements of the system are a high performance MIMO RADAR sensor, an optical camera and a dedicated set of software algorithms encompassing interferometry, tomography and photogrammetry. The MIMO Radar sensor proposed in this work, provides an extremely high sensitivity to displacements making the system able to react to tiny deformations (up to tens of microns) with a time scale which spans from milliseconds to hours. The MIMO feature of the system makes the system capable of providing a set of two-dimensional images of the observed scene, each mapped on the azimuth-range directions with noticeably resolution in both the dimensions and with an outstanding repetition rate. The back-scattered energy, which is distributed in the 3D space, is projected on a 2D plane, where each pixel has as coordinates the Line-Of-Sight distance and the cross-range azimuthal angle. At the same time, the high performing processing unit allows to sense the observed scene with remarkable refresh periods (up to milliseconds), thus opening the way for combined static and dynamic structural health monitoring. Thanks to the smart TX/RX antenna array layout, the MIMO data can be processed through a tomographic approach to reconstruct the three-dimensional map of the observed scene. This 3D point cloud is then accurately mapped on a 2D digital optical image through photogrammetric techniques, allowing for easy and straightforward interpretations of the measurements. Once the three-dimensional image is reconstructed, a 'repeat-pass' interferometric approach is exploited to provide the user of the system with high frequency three-dimensional motion/vibration estimation of each point of the reconstructed image. At this stage, the methodology leverages consolidated atmospheric correction algorithms to provide reliable displacement and vibration measurements.

Keywords: Interferometry, MIMO RADAR, SAR, tomography.

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Authors: Ghassan Kbar, Shady Aly, Ibraheem Elsharawy, Akshay Bhatia, Nur Alhasan, Ronaldo Enriquez

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The Smart Help for persons with disability (PWD) is a part of the project SMARTDISABLE which aims to develop relevant solution for PWD that target to provide an adequate workplace environment for them. It would support PWD needs smartly through smart help to allow them access to relevant information and communicate with other effectively and flexibly, and smart editor that assist them in their daily work. It will assist PWD in knowledge processing and creation as well as being able to be productive at the work place. The technical work of the project involves design of a technological scenario for the Ambient Intelligence (AmI) - based assistive technologies at the workplace consisting of an integrated universal smart solution that suits many different impairment conditions and will be designed to empower the Physically disabled persons (PDP) with the capability to access and effectively utilize the ICTs in order to execute knowledge rich working tasks with minimum efforts and with sufficient comfort level. The proposed technology solution for PWD will support voice recognition along with normal keyboard and mouse to control the smart help and smart editor with dynamic auto display interface that satisfies the requirements for different PWD group. In addition, a smart help will provide intelligent intervention based on the behavior of PWD to guide them and warn them about possible misbehavior. PWD can communicate with others using Voice over IP controlled by voice recognition. Moreover, Auto Emergency Help Response would be supported to assist PWD in case of emergency. This proposed technology solution intended to make PWD very effective at the work environment and flexible using voice to conduct their tasks at the work environment. The proposed solution aims to provide favorable outcomes that assist PWD at the work place, with the opportunity to participate in PWD assistive technology innovation market which is still small and rapidly growing as well as upgrading their quality of life to become similar to the normal people at the workplace. Finally, the proposed smart help solution is applicable in all workplace setting, including offices, manufacturing, hospital, etc.

Keywords: Ambient Intelligence, ICT, Persons with disability PWD, Smart application.

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Authors: Terna T. Paul, Iloechuba P. Ngozika

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A study was carried out to evaluate the growth and yield performance of Pleurotus ostreatus spawn on different organic substrates in Lafia, Nasarawa State, Nigeria. 50 g each of four different substrates namely; corncobs, rice straw, sugarcane bagasse and sawdust sourced locally from farmlands and processing sites, were amended with 2% calcium carbonate and calcium sulphide and sterilized using three sterilization methods namely; hot water, steam, and lime. Five grams of P. ostreatus spawn were inoculated unto treated substrates, incubated in the dark for 16 days and in light for 19 days at 25 ⁰C for the commencement of pinhead and fruit body formations respectively. Growth and yield parameters such as days to full colonization, days to pinhead formation and days to fruit body formation were recorded. Cap diameter and fresh weight of mature mushrooms were also measured for a total count of four flushes. P. ostreatus spawn grown on sugarcane bagasse recorded the highest mean cap diameter (4.69 cm), highest mean fresh weight (34.68 g), highest biological efficiency (69.37%) and highest production rate (2.83 g per day). Spawn grown on rice straw recorded the least number of days to full substrate colonization (11.00). Spawn grown on corn cobs recorded the least mean number of days to pin head (18.75) and fruiting body formations (20.25). There were no significant differences (P ≤ 0.05) among the evaluated substrates with respect to growth and yield performance of P. ostreatus. Substrates sterilized with hot water supported the highest mean cap diameter (5.64 cm), highest biological efficiency (87.04%) and highest production rate (3.43 g per day) of P. ostreatus. Significant differences (P ≤ 0.05) were observed in cap diameter, fresh weight, biological efficiency and production rates among the evaluated sterilization methods. Hot water sterilization of sugarcane bagasse could be adopted for enhanced yield of oyster mushrooms, especially among indigent farming communities in Nigeria and beyond.

Keywords: Agro wastes, growth, Pleurotus ostreatus, sterilization methods, yield.

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Authors: Nicole M. Martino

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Reinforced concrete bridge deck condition assessments primarily use visual inspection methods, where an inspector looks for and records locations of cracks, potholes, efflorescence and other signs of probable deterioration. Sounding is another technique used to diagnose the condition of a bridge deck, however this method listens for damage within the subsurface as the surface is struck with a hammer or chain. Even though extensive procedures are in place for using these inspection techniques, neither one provides the inspector with a comprehensive understanding of the internal condition of a bridge deck – the location where damage originates from.  In order to make accurate estimates of repair locations and quantities, in addition to allocating the necessary funding, a total understanding of the deck’s deteriorated state is key. The research presented in this paper collected infrared thermography and ground penetrating radar data from reinforced concrete bridge decks without an asphalt overlay. These decks were of various ages and their condition varied from brand new, to in need of replacement. The goals of this work were to first verify that these nondestructive evaluation methods could identify similar areas of healthy and damaged concrete, and then to see if combining the results of both methods would provide a higher confidence than if the condition assessment was completed using only one method. The results from each method were presented as plan view color contour plots. The results from one of the decks assessed as a part of this research, including these plan view plots, are presented in this paper. Furthermore, in order to answer the interest of transportation agencies throughout the United States, this research developed a step-by-step guide which demonstrates how to collect and assess a bridge deck using these nondestructive evaluation methods. This guide addresses setup procedures on the deck during the day of data collection, system setups and settings for different bridge decks, data post-processing for each method, and data visualization and quantification.

Keywords: Bridge deck deterioration, ground penetrating radar, infrared thermography, NDT of bridge decks.

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Authors: N. Stevulova, I. Schwarzova, V. Hospodarova, J. Junak, J. Briancin

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Sustainability is becoming a priority for developers and the use of environmentally friendly materials is increasing. Nowadays, the application of raw materials from renewable sources to building materials has gained a significant interest in this research area. Lignocellulosic aggregates and cellulosic fibers are coming from many different sources such as wood, plants and waste. They are promising alternative materials to replace synthetic, glass and asbestos fibers as reinforcement in inorganic matrix of composites. Natural fibers are renewable resources so their cost is relatively low in comparison to synthetic fibers. With the consideration of environmental consciousness, natural fibers are biodegradable so their using can reduce CO₂ emissions in the building materials production. The use of cellulosic fibers in cementitious matrices have gained importance because they make the composites lighter at high fiber content, they have comparable cost - performance ratios to similar building materials and they could be processed from waste paper, thus expanding the opportunities for waste utilization in cementitious materials. The main objective of this work is to find out the possibility of using different wastes: hemp hurds as waste of hemp stem processing and recycled fibers obtained from waste paper for making cement composite products such as mortars based on cellulose fibers. This material was made of cement mortar containing organic filler based on hemp hurds and recycled waste paper. In addition, the effects of fibers and their contents on some selected physical and mechanical properties of the fiber-cement plaster composites have been investigated. In this research organic material have used to mortars as 2.0, 5.0 and 10.0 % replacement of cement weight. Reference sample is made for comparison of physical and mechanical properties of cement composites based on recycled cellulosic fibers and lignocellulosic aggregates. The prepared specimens were tested after 28 days of curing in order to investigate density, compressive strength and water absorbability. Scanning Electron Microscopy examination was also carried out.

Keywords: Hemp hurds, organic filler, recycled paper, sustainable building materials.

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Authors: M. A. Stoian, D. M. Cocarta, A. Badea

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The main sources of soil pollution due to petroleum contaminants are industrial processes involve crude oil. Soil polluted with crude oil is toxic for plants, animals, and humans. Human exposure to the contaminated soil occurs through different exposure pathways: Soil ingestion, diet, inhalation, and dermal contact. The present study research is focused on soil contamination with heavy metals as a consequence of soil pollution with petroleum products. Human exposure pathways considered are: Accidentally ingestion of contaminated soil and dermal contact. The purpose of the paper is to identify the human health risk (carcinogenic risk) from soil contaminated with heavy metals. The human exposure and risk were evaluated for five contaminants of concern of the eleven which were identified in soil. Two soil samples were collected from a bioremediation platform from Muntenia Region of Romania. The soil deposited on the bioremediation platform was contaminated through extraction and oil processing. For the research work, two average soil samples from two different plots were analyzed: The first one was slightly contaminated with petroleum products (Total Petroleum Hydrocarbons (TPH) in soil was 1420 mg/kg_d.w.), while the second one was highly contaminated (TPH in soil was 24306 mg/kg_d.w.). In order to evaluate risks posed by heavy metals due soil pollution with petroleum products, five metals known as carcinogenic were investigated: Arsenic (As), Cadmium (Cd), Chromium^VI (Cr^VI), Nickel (Ni), and Lead (Pb). Results of the chemical analysis performed on samples collected from the contaminated soil evidence soil contamination with heavy metals as following: As in Site 1 = 6.96 mg/kg_d.w; As in Site 2 = 11.62 mg/kg_d.w, Cd in Site 1 = 0.9 mg/kg_d.w; Cd in Site 2 = 1 mg/kg_d.w; Cr^VI was 0.1 mg/kg_d.w for both sites; Ni in Site 1 = 37.00 mg/kg_d.w; Ni in Site 2 = 42.46 mg/kg_d.w; Pb in Site 1 = 34.67 mg/kg_d.w; Pb in Site 2 = 120.44 mg/kg_d.w. The concentrations for these metals exceed the normal values established in the Romanian regulation, but are smaller than the alert level for a less sensitive use of soil (industrial). Although, the concentrations do not exceed the thresholds, the next step was to assess the human health risk posed by soil contamination with these heavy metals. Results for risk were compared with the acceptable one (10^-6, according to World Human Organization). As, expected, the highest risk was identified for the soil with a higher degree of contamination: Individual Risk (IR) was 1.11×10^-5 compared with 8.61×10^-6. 

Keywords: Carcinogenic risk, heavy metals, human health risk assessment, soil pollution.

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Authors: P. Bogas

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As a scientific contribution to this discussion, a pedagogical intervention of a quasi-experimental nature was developed, with a mixed methodology, evaluating the intervention within a single curricular unit of Marketing, using cases based on real challenges of brands, business simulation and customer projects. Primary and secondary experiences were incorporated in the intervention: the primary experiences are the experiential activities themselves; the secondary experiences resulted from the primary experience, such as reflection and discussion in work teams. A diversified learning relationship was encouraged through the various connections between the different members of the learning community. The present study concludes that in the same context, the students' response can be described as: students who reinforce the initial deep approach, students who maintain the initial deep approach level and others who change from an emphasis on the deep approach to one closer to superficial. This typology did not always confirm studies reported in the literature, namely, whether the initial level of deep processing would influence the superficial and the opposite. The result of this investigation points to the inclusion of pedagogical and didactic activities that integrate different motivations and initial strategies, leading to a possible adoption of deep approaches to learning, since it revealed statistically significant differences in the difference in the scores of the deep/superficial approach and the experiential level. In the case of real challenges, the categories of “attribution of meaning and meaning of studied” and the possibility of “contact with an aspirational context” for their future professional stand out. In this category, the dimensions of autonomy that will be required of them were also revealed when comparing the classroom context of real cases and the future professional context and the impact they may have on the world. Regarding to the simulated practice, two categories of response stand out: on the one hand, the motivation associated with the possibility of measuring the results of the decisions taken, an awareness of oneself and, on the other hand, the additional effort that this practice required for some of the students.

Keywords: Experiential learning, higher education, marketing, mixed methods, reflective thinking.

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